Haystack

Haystack is an open-source framework for building NLP applications such as semantic search, question answering, RAG, and agents. It is designed for developers, ML engineers, and data teams who want to integrate language models into products or internal tools in a reliable, production-ready way.

Haystack itself is open-source and free to use under its respective license. However, some components you plug in—such as commercial LLM APIs, managed vector databases, or cloud infrastructure—may incur separate costs that depend on your chosen providers.

Haystack is model- and storage-agnostic. It supports OpenAI-style and open-source LLMs, common embedding models, and integrates with popular document and vector stores such as Elasticsearch, OpenSearch, and various vector databases. You can swap components without rewriting your entire pipeline.

Yes. Haystack is designed with production in mind, offering components for scalable retrieval, caching, monitoring, and evaluation. Its modular architecture helps you run pipelines in containers, orchestrators, or microservices, and evolve them as your traffic and requirements grow.

You do not need to be an NLP researcher. Basic software engineering skills and familiarity with Python are usually enough to start building pipelines. Haystack offers clear abstractions, examples, and documentation that help you adopt best practices without dealing with every low-level detail.